Refactoring with Codemods to Automate API Adjustments

Clear a Stale Function Toggle

Let’s begin with a easy but sensible instance to display the
energy of codemods. Think about you’re utilizing a characteristic
toggle in your
codebase to manage the discharge of unfinished or experimental options.
As soon as the characteristic is stay in manufacturing and dealing as anticipated, the subsequent
logical step is to wash up the toggle and any associated logic.

For example, think about the next code:

const information = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;

As soon as the characteristic is totally launched and now not wants a toggle, this
may be simplified to:

const information = { identify: 'Product' };

The duty entails discovering all cases of featureToggle within the
codebase, checking whether or not the toggle refers to
feature-new-product-list, and eradicating the conditional logic surrounding
it. On the similar time, different characteristic toggles (like
feature-search-result-refinement, which can nonetheless be in improvement)
ought to stay untouched. The codemod must perceive the construction
of the code to use modifications selectively.

Understanding the AST

Earlier than we dive into writing the codemod, let’s break down how this
particular code snippet appears in an AST. You should use instruments like AST
Explorer to visualise how supply code and AST
are mapped. It’s useful to know the node sorts you are interacting
with earlier than making use of any modifications.

The picture under exhibits the syntax tree by way of ECMAScript syntax. It
accommodates nodes like Identifier (for variables), StringLiteral (for the
toggle identify), and extra summary nodes like CallExpression and
ConditionalExpression.

Determine 2: The Summary Syntax Tree illustration of the characteristic toggle examine

On this AST illustration, the variable information is assigned utilizing a
ConditionalExpression. The take a look at a part of the expression calls
featureToggle('feature-new-product-list'). If the take a look at returns true,
the consequent department assigns { identify: 'Product' } to information. If
false, the alternate department assigns undefined.

For a job with clear enter and output, I choose writing assessments first,
then implementing the codemod. I begin by defining a unfavorable case to
guarantee we don’t by chance change issues we wish to depart untouched,
adopted by an actual case that performs the precise conversion. I start with
a easy state of affairs, implement it, then add a variation (like checking if
featureToggle is known as inside an if assertion), implement that case, and
guarantee all assessments go.

This strategy aligns properly with Check-Pushed Growth (TDD), even
in the event you don’t apply TDD frequently. Realizing precisely what the
transformation’s inputs and outputs are earlier than coding improves security and
effectivity, particularly when tweaking codemods.

With jscodeshift, you possibly can write assessments to confirm how the codemod
behaves:

const remodel = require("../remove-feature-new-product-list");

defineInlineTest(
  remodel,
  {},
  `
  const information = featureToggle('feature-new-product-list') ? { identify: 'Product' } : undefined;
  `,
  `
  const information = { identify: 'Product' };
  `,
  "delete the toggle feature-new-product-list in conditional operator"
);

The defineInlineTest operate from jscodeshift lets you outline
the enter, anticipated output, and a string describing the take a look at’s intent.
Now, working the take a look at with a traditional jest command will fail as a result of the
codemod isn’t written but.

The corresponding unfavorable case would make sure the code stays unchanged
for different characteristic toggles:

defineInlineTest(
  remodel,
  {},
  `
  const information = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;
  `,
  `
  const information = featureToggle('feature-search-result-refinement') ? { identify: 'Product' } : undefined;
  `,
  "don't change different characteristic toggles"
);

Writing the Codemod

Let’s begin by defining a easy remodel operate. Create a file
referred to as remodel.js with the next code construction:

module.exports = operate(fileInfo, api, choices) {
  const j = api.jscodeshift;
  const root = j(fileInfo.supply);

  // manipulate the tree nodes right here

  return root.toSource();
};

This operate reads the file right into a tree and makes use of jscodeshift’s API to
question, modify, and replace the nodes. Lastly, it converts the AST again to
supply code with .toSource().

Now we will begin implementing the remodel steps:

1. Discover all cases of featureToggle.
2. Confirm that the argument handed is 'feature-new-product-list'.
3. Exchange your entire conditional expression with the consequent half,
   successfully eradicating the toggle.

Right here’s how we obtain this utilizing jscodeshift:

module.exports = operate (fileInfo, api, choices) {
  const j = api.jscodeshift;
  const root = j(fileInfo.supply);

  // Discover ConditionalExpression the place the take a look at is featureToggle('feature-new-product-list')
  root
    .discover(j.ConditionalExpression, {
      take a look at: {
        callee: { identify: "featureToggle" },
        arguments: [{ value: "feature-new-product-list" }],
      },
    })
    .forEach((path) => {
      // Exchange the ConditionalExpression with the 'consequent'
      j(path).replaceWith(path.node.consequent);
    });

  return root.toSource();
};

The codemod above:

• Finds ConditionalExpression nodes the place the take a look at calls
  featureToggle('feature-new-product-list').
• Replaces your entire conditional expression with the ensuing (i.e., {
identify: 'Product' }), eradicating the toggle logic and leaving simplified code
  behind.

This instance demonstrates how straightforward it’s to create a helpful
transformation and apply it to a big codebase, considerably lowering
guide effort.

You’ll want to put in writing extra take a look at instances to deal with variations like
if-else statements, logical expressions (e.g.,
!featureToggle('feature-new-product-list')), and so forth to make the
codemod strong in real-world eventualities.

As soon as the codemod is prepared, you possibly can check it out on a goal codebase,
such because the one you are engaged on. jscodeshift offers a command-line
instrument that you should use to use the codemod and report the outcomes.

$ jscodeshift -t transform-name src/

After validating the outcomes, examine that each one useful assessments nonetheless
go and that nothing breaks—even in the event you’re introducing a breaking change.
As soon as glad, you possibly can commit the modifications and lift a pull request as
a part of your regular workflow.

Codemods Enhance Code High quality and Maintainability

Codemods aren’t simply helpful for managing breaking API modifications—they’ll
considerably enhance code high quality and maintainability. As codebases
evolve, they typically accumulate technical debt, together with outdated characteristic
toggles, deprecated strategies, or tightly coupled elements. Manually
refactoring these areas may be time-consuming and error-prone.

By automating refactoring duties, codemods assist maintain your codebase clear
and freed from legacy patterns. Often making use of codemods lets you
implement new coding requirements, take away unused code, and modernize your
codebase with out having to manually modify each file.

Refactoring an Avatar Part

Now, let’s have a look at a extra complicated instance. Suppose you’re working with
a design system that features an Avatar element tightly coupled with a
Tooltip. At any time when a consumer passes a identify prop into the Avatar, it
routinely wraps the avatar with a tooltip.

Determine 3: A avatar element with a tooltip

Right here’s the present Avatar implementation:

import { Tooltip } from "@design-system/tooltip";

const Avatar = ({ identify, picture }: AvatarProps) => {
  if (identify) {
    return (
      
        
      
    );
  }

  return ;
};

The objective is to decouple the Tooltip from the Avatar element,
giving builders extra flexibility. Builders ought to have the ability to determine
whether or not to wrap the Avatar in a Tooltip. Within the refactored model,
Avatar will merely render the picture, and customers can apply a Tooltip
manually if wanted.

Right here’s the refactored model of Avatar:

const Avatar = ({ picture }: AvatarProps) => {
  return ;
};

Now, customers can manually wrap the Avatar with a Tooltip as
wanted:

import { Tooltip } from "@design-system/tooltip";
import { Avatar } from "@design-system/avatar";

const UserProfile = () => {
  return (
    
      
    
  );
};

The problem arises when there are a whole lot of Avatar usages unfold
throughout the codebase. Manually refactoring every occasion can be extremely
inefficient, so we will use a codemod to automate this course of.

Utilizing instruments like AST Explorer, we will
examine the element and see which nodes characterize the Avatar utilization
we’re focusing on. An Avatar element with each identify and picture props
is parsed into an summary syntax tree as proven under:

Determine 4: AST of the Avatar element utilization

Writing the Codemod

Let’s break down the transformation into smaller duties:

• Discover Avatar utilization within the element tree.
• Test if the identify prop is current.
• If not, do nothing.
• If current:
• Create a Tooltip node.
• Add the identify to the Tooltip.
• Take away the identify from Avatar.
• Add Avatar as a baby of the Tooltip.
• Exchange the unique Avatar node with the brand new Tooltip.

To start, we’ll discover all cases of Avatar (I’ll omit a few of the
assessments, however you need to write comparability assessments first).

defineInlineTest(
    { default: remodel, parser: "tsx" },
    {},
    `
    
    `,
    `
    
      
    
    `,
    "wrap avatar with tooltip when identify is offered"
  );

Much like the featureToggle instance, we will use root.discover with
search standards to find all Avatar nodes:

root
  .discover(j.JSXElement, {
    openingElement: { identify: { identify: "Avatar" } },
  })
  .forEach((path) => {
    // now we will deal with every Avatar occasion
  });

Subsequent, we examine if the identify prop is current:

root
  .discover(j.JSXElement, {
    openingElement: { identify: { identify: "Avatar" } },
  })
  .forEach((path) => {
    const avatarNode = path.node;

    const nameAttr = avatarNode.openingElement.attributes.discover(
      (attr) => attr.identify.identify === "identify"
    );

    if (nameAttr) {
      const tooltipElement = createTooltipElement(
        nameAttr.worth.worth,
        avatarNode
      );
      j(path).replaceWith(tooltipElement);
    }
  });

For the createTooltipElement operate, we use the
jscodeshift API to create a brand new JSX node, with the identify
prop utilized to the Tooltip and the Avatar
element as a baby. Lastly, we name replaceWith to
substitute the present path.

Right here’s a preview of the way it appears in
Hypermod, the place the codemod is written on
the left. The highest half on the precise is the unique code, and the underside
half is the remodeled outcome:

Determine 5: Run checks inside hypermod earlier than apply it to your codebase

This codemod searches for all cases of Avatar. If a
identify prop is discovered, it removes the identify prop
from Avatar, wraps the Avatar inside a
Tooltip, and passes the identify prop to the
Tooltip.

By now, I hope it’s clear that codemods are extremely helpful and
that the workflow is intuitive, particularly for large-scale modifications the place
guide updates can be an enormous burden. Nonetheless, that is not the entire
image. Within the subsequent part, I’ll make clear a few of the challenges
and the way we will handle these less-than-ideal points.

Leveraging Supply Graphs and Check-Pushed Codemods

To deal with these complexities, codemods needs to be used alongside different
strategies. For example, a couple of years in the past, I participated in a design
system elements rewrite undertaking at Atlassian. We addressed this subject by
first looking the supply graph, which contained the vast majority of inner
element utilization. This allowed us to know how elements have been used,
whether or not they have been imported beneath completely different names, or whether or not sure
public props have been continuously used. After this search part, we wrote our
take a look at instances upfront, guaranteeing we coated the vast majority of use instances, and
then developed the codemod.

In conditions the place we could not confidently automate the improve, we
inserted feedback or “TODOs” on the name websites. This allowed the
builders working the script to deal with particular instances manually. Often,
there have been solely a handful of such cases, so this strategy nonetheless proved
helpful for upgrading variations.

Using Current Code Standardization Instruments

As you possibly can see, there are many edge instances to deal with, particularly in
codebases past your management—similar to exterior dependencies. This
complexity implies that utilizing codemods requires cautious supervision and a
evaluation of the outcomes.

Nonetheless, in case your codebase has standardization instruments in place, similar to a
linter that enforces a selected coding type, you possibly can leverage these
instruments to cut back edge instances. By imposing a constant construction, instruments
like linters assist slim down the variations in code, making the
transformation simpler and minimizing surprising points.

For example, you may use linting guidelines to limit sure patterns,
similar to avoiding nested conditional (ternary) operators or imposing named
exports over default exports. These guidelines assist streamline the codebase,
making codemods extra predictable and efficient.

Moreover, breaking down complicated transformations into smaller, extra
manageable ones lets you sort out particular person points extra exactly. As
we’ll quickly see, composing smaller codemods could make dealing with complicated
modifications extra possible.

Codemod Composition

Let’s revisit the characteristic toggle removing instance mentioned earlier. Within the code snippet
we have now a toggle referred to as feature-convert-new have to be eliminated:

import { featureToggle } from "./utils/featureToggle";

const convertOld = (enter: string) => {
  return enter.toLowerCase();
};

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const outcome = featureToggle("feature-convert-new")
  ? convertNew("Hi there, world")
  : convertOld("Hi there, world");

console.log(outcome);

The codemod for take away a given toggle works nice, and after working the codemod,
we would like the supply to appear to be this:

const convertNew = (enter: string) => {
  return enter.toUpperCase();
};

const outcome = convertNew("Hi there, world");

console.log(outcome);

Nonetheless, past eradicating the characteristic toggle logic, there are extra duties to
deal with:

• Take away the unused convertOld operate.
• Clear up the unused featureToggle import.

In fact, you may write one huge codemod to deal with every part in a
single go and take a look at it collectively. Nonetheless, a extra maintainable strategy is
to deal with codemod logic like product code: break the duty into smaller,
impartial items—similar to how you’ll usually refactor manufacturing
code.

Breaking It Down

We will break the large transformation down into smaller codemods and
compose them. The benefit of this strategy is that every transformation
may be examined individually, overlaying completely different instances with out interference.
Furthermore, it lets you reuse and compose them for various
functions.

For example, you may break it down like this:

• A change to take away a particular characteristic toggle.
• One other transformation to wash up unused imports.
• A change to take away unused operate declarations.

By composing these, you possibly can create a pipeline of transformations:

import { removeFeatureToggle } from "./remove-feature-toggle";
import { removeUnusedImport } from "./remove-unused-import";
import { removeUnusedFunction } from "./remove-unused-function";

import { createTransformer } from "./utils";

const removeFeatureConvertNew = removeFeatureToggle("feature-convert-new");

const remodel = createTransformer([
  removeFeatureConvertNew,
  removeUnusedImport,
  removeUnusedFunction,
]);

export default remodel;

On this pipeline, the transformations work as follows:

1. Take away the feature-convert-new toggle.
2. Clear up the unused import assertion.
3. Take away the convertOld operate because it’s now not used.

Determine 6: Compose transforms into a brand new remodel

It’s also possible to extract extra codemods as wanted, combining them in
numerous orders relying on the specified consequence.

Determine 7: Put completely different transforms right into a pipepline to kind one other remodel

The createTransformer Perform

The implementation of the createTransformer operate is comparatively
simple. It acts as a higher-order operate that takes a listing of
smaller remodel capabilities, iterates via the record to use them to
the basis AST, and at last converts the modified AST again into supply
code.

import { API, Assortment, FileInfo, JSCodeshift, Choices } from "jscodeshift";

sort TransformFunction = { (j: JSCodeshift, root: Assortment): void };

const createTransformer =
  (transforms: TransformFunction[]) =>
  (fileInfo: FileInfo, api: API, choices: Choices) => {
    const j = api.jscodeshift;
    const root = j(fileInfo.supply);

    transforms.forEach((remodel) => remodel(j, root));
    return root.toSource(choices.printOptions || { quote: "single" });
  };

export { createTransformer };

For instance, you may have a remodel operate that inlines
expressions assigning the characteristic toggle name to a variable, so in later
transforms you don’t have to fret about these instances anymore:

const shouldEnableNewFeature = featureToggle('feature-convert-new');

if (!shouldEnableNewFeature && someOtherLogic) {
  //...
}

Turns into this:

if (!featureToggle('feature-convert-new') && someOtherLogic) {
  //...
}

Over time, you may construct up a set of reusable, smaller
transforms, which might tremendously ease the method of dealing with tough edge
instances. This strategy proved extremely efficient in our work refining design
system elements. As soon as we transformed one package deal—such because the button
element—we had a couple of reusable transforms outlined, like including feedback
firstly of capabilities, eradicating deprecated props, or creating aliases
when a package deal is already imported above.

Every of those smaller transforms may be examined and used independently
or mixed for extra complicated transformations, which hastens subsequent
conversions considerably. In consequence, our refinement work grew to become extra
environment friendly, and these generic codemods are actually relevant to different inner
and even exterior React codebases.

Since every remodel is comparatively standalone, you possibly can fine-tune them
with out affecting different transforms or the extra complicated, composed ones. For
occasion, you may re-implement a remodel to enhance efficiency—like
lowering the variety of node-finding rounds—and with complete take a look at
protection, you are able to do this confidently and safely.